The ANL test is a suitable tool for measuring the advantage of one NRA. A prediction of the measured individual ΔANL failed. However, mean DANL could be predicted with some methods. Furthermore, the individual hearing loss should be taken into account for a more accurate prediction for hearing-impaired subjects.

A dead region is a region in the cochlea where the inner hair cells and/or the auditory neurones are functioning very poorly, if at all. People who are being considered for a combination of a cochlear implant and a hearing aid typically have a dead region in the parts of the cochlea that normally respond to medium and high frequencies, but have some functional hearing at lower frequencies. For such people, it may be useful to determine the edge frequency, f(e), of any dead region. This may be relevant to choosing the most appropriate insertion depth of the electrode array, and to the way that frequencies in the input signal are mapped to acoustic and electric stimulation. It may also be helpful in interpreting the results of research studies. This paper reviews methods for diagnosing dead regions and defining the value of f(e). It is argued that the value of f(e) cannot be determined reliably from the audiogram, although a dead region is likely to be present at a given frequency when the hearing loss at that frequency is 70 dB or more. When a sinusoidal signal is reported as sounding highly distorted or noise-like, a dead region may be present at the signal frequency, but again this is not a reliable indicator. The TEN test is a simple clinical method for diagnosis of dead regions. Where this test gives a positive diagnosis, it is recommended that psychophysical tuning curves be measured to define the value of f(e) more precisely.

Short-term and long-term learning effects were investigated for the German Oldenburg sentence test (OLSA) using original and time-compressed fast speech in noise. Normal-hearing and hearing-impaired participants completed six lists of the OLSA in five sessions. Two groups of normal-hearing listeners (24 and 12 listeners) and two groups of hearing-impaired listeners (9 listeners each) performed the test with original or time-compressed speech. In general, original speech resulted in better speech recognition thresholds than time-compressed speech. Thresholds decreased with repetition for both speech materials. Confirming earlier results, the largest improvements were observed within the first measurements of the first session, indicating a rapid initial adaptation phase. The improvements were larger for time-compressed than for original speech. The novel results on long-term learning effects when using the OLSA indicate a longer phase of ongoing learning, especially for time-compressed speech, which seems to be limited by a floor effect. In addition, for normal-hearing participants, no complete transfer of learning benefits from time-compressed to original speech was observed. These effects should be borne in mind when inviting listeners repeatedly, for example, in research settings.

For assessing hearing aid algorithms, a method is sought to shift the threshold of a speech-in-noise test to (mostly positive) signal-to-noise ratios (SNRs) that allow discrimination across algorithmic settings and are most relevant for hearing-impaired listeners in daily life. Hence, time-compressed speech with higher speech rates was evaluated to parametrically increase the difficulty of the test while preserving most of the relevant acoustical speech cues. A uniform and a non-uniform algorithm were used to compress the sentences of the German Oldenburg Sentence Test at different speech rates. In comparison, the non-uniform algorithm exhibited greater deviations from the targeted time compression, as well as greater changes of the phoneme duration, spectra, and modulation spectra. Speech intelligibility for fast Oldenburg sentences in background noise at different SNRs was determined with 48 normal-hearing listeners. The results confirmed decreasing intelligibility with increasing speech rate. Speech had to be compressed to more than 30% of its original length to reach 50% intelligibility at positive SNRs. Characteristics influencing the discrimination ability of the test for assessing effective SNR changes were investigated. Subjective and objective measures indicated a clear advantage of the uniform algorithm in comparison to the non-uniform algorithm for the application in speech-in-noise tests.